Topic Menu

Topic Editors

E-Mail Website

1. College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China
2. National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai University, Nanjing 210098, China

Prof. Dr. Lei Tang

E-Mail Website

Nanjing Hydraulic Research Institute, Nanjing 210029, China

Dr. Meng Yang

E-Mail Website

1. Nanjing Hydraulic Research Institute, Nanjing 210029, China
2. College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China

Structural Health Monitoring Based on Materials, Mathematical Methods, and Sensing Technology

Abstract submission deadline

closed (20 October 2023)

Manuscript submission deadline

closed (20 December 2023)

Viewed by

9805

Topic Information

Dear Colleagues,

Recent advances in materials, mathematical methods, and sensing technology have opened vast possibilities for the development of disruptive innovations in the field of structural health monitoring.

Nowadays, we can find SHM and its applications being used in various structures with very different requirements. The field of SHM involves a wide range of transdisciplinary areas, including various repair and construction materials, embedded and surface sensors and actuators, damage diagnosis and prognosis, signal and image processing, data interpretation, machine learning, data fusion, energy harvesting, etc. There has been a large and increasing volume of research on SHM based on materials, mathematical methods, and sensing technology. Structural health monitoring (SHM) and related research have gained significant importance for civil, mechanical, aerospace, and offshore structures as they present various cutting-edge achievements to share and promote the development and progress of structural health monitoring technology. However, new and advanced materials, mathematical methods, and sensing technology are not currently being presented and studied for discussion when considering present improvements in safety awareness and increased monitoring information. Thus, for the successful development of SHM using new materials for large and complex structures, techniques should be enhanced. In addition, mathematical methods for signal/data processing plays an important role in the implementation of SHM technologies.

Accurate and regionalized sensing technology for the massive amount of data generated through the long-term monitoring of large and complex structures (e.g., dams, bridges, embankments buildings, ships, aircrafts, wind turbines, pipes, etc.) has become an emerging challenge that needs to be addressed by the community. New ideas provide advanced frameworks and algorithms that can help to discover and model the performance and conditions of a structure through deep mining of materials, mathematical methods, and sensing technology. This Special Issue will publish study results and research papers that present innovative uses of materials, mathematical methods, and sensing technology for processing structural health monitoring. Additionally, we also encourage papers that provide comprehensive reviews of the literature on this topic. We cordially invite you to submit your classic and novel research for consideration. Suitable topics include:

SHM for dams, bridges, embankments, aerospace, offshore infrastructures, etc.;
Advanced materials for SHM technology in composite, steel, and concrete structures;
Accurate and regionalized monitoring methods for different structures;
Localised monitoring and damage detection;
Various methods for solving the deployment problem of SHM technology;
New data processing methods for SHM;
General research for SHM in terms of materials, mathematical methods, and sensing technology;
Other any relatively valuable researches about SHM.

Prof. Dr. Chongshi Gu
Prof. Dr. Lei Tang
Dr. Meng Yang
Topic Editors

Keywords

structural health monitoring
advanced material
mathematical method
damage detection
sensing technology
embedded and surface sensors and actuators
composite structures
steel structures
reinforced concrete structures
numerical simulation
physical model
optical fiber

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Applied Sciences applsci	2.7	4.5	2011	16.9 Days	CHF 2400
Buildings buildings	3.8	3.1	2011	14.6 Days	CHF 2600
CivilEng civileng	-	2.0	2020	37.7 Days	CHF 1200
Materials materials	3.4	5.2	2008	13.9 Days	CHF 2600
Remote Sensing remotesensing	5.0	7.9	2009	23 Days	CHF 2700
Sensors sensors	3.9	6.8	2001	17 Days	CHF 2600

Preprints.org is a multidiscipline platform providing preprint service that is dedicated to sharing your research from the start and empowering your research journey.

MDPI Topics is cooperating with Preprints.org and has built a direct connection between MDPI journals and Preprints.org. Authors are encouraged to enjoy the benefits by posting a preprint at Preprints.org prior to publication:

Immediately share your ideas ahead of publication and establish your research priority;
Protect your idea from being stolen with this time-stamped preprint article;
Enhance the exposure and impact of your research;
Receive feedback from your peers in advance;
Have it indexed in Web of Science (Preprint Citation Index), Google Scholar, Crossref, SHARE, PrePubMed, Scilit and Europe PMC.

Published Papers (12 papers)

Download All Papers

Order results

Result details

Journals

Show export options Show export options

Select all

Export citation of selected articles as:

28 pages, 27541 KiB

Open AccessArticle

Case Studies about Finite Element Modeling and Wireless Sensing of Three Pennsylvania Bridges

by Alireza Enshaeian, Behzad Ghahremani and Piervincenzo Rizzo

Sensors 2024, 24(6), 1714; https://doi.org/10.3390/s24061714 - 07 Mar 2024

Viewed by 435

Abstract

Three Pennsylvanian bridges were studied using finite element and wireless sensor technology. A detailed finite element model of each bridge was created using a commercial software in order to calculate the strains generated by a load that simulates the presence of a standard truck. Pristine and damage scenarios were simulated, and the computed strains were compared to the experimental strains measured with proprietary wireless sensors during a truck test performed by companies not involved in the study presented in this article. The comparison demonstrated the accuracy of the model and the presence of a few non-critical anomalies in terms of load redistribution. In addition, the comparison proved the reliability of the wireless sensing system installed on the bridges, although some drift was observed. The structural monitoring program for the three bridges was also evaluated by processing more than two years of data streamed to a repository. Full article

(This article belongs to the Topic Structural Health Monitoring Based on Materials, Mathematical Methods, and Sensing Technology)

► Show Figures

Figure 1

18 pages, 3839 KiB

Open AccessArticle

Wireless Passive Ceramic Sensor for Far-Field Temperature Measurement at High Temperatures

by Kevin M. Tennant, Brian R. Jordan, Noah L. Strader, Kavin Sivaneri Varadharajan Idhaiam, Mark Jerabek, Jay Wilhelm, Daryl S. Reynolds and Edward M. Sabolsky

Sensors 2024, 24(5), 1407; https://doi.org/10.3390/s24051407 - 22 Feb 2024

Viewed by 447

Abstract

A passive wireless high-temperature sensor for far-field applications was developed for stable temperature sensing up to 1000 °C. The goal is to leverage the properties of electroceramic materials, including adequate electrical conductivity, high-temperature resilience, and chemical stability in harsh environments. Initial sensors were fabricated using Ag for operation to 600 °C to achieve a baseline understanding of temperature sensing principles using patch antenna designs. Fabrication then followed with higher temperature sensors made from (In, Sn) O₂ (ITO) for evaluation up to 1000 °C. A patch antenna was modeled in ANSYS HFSS to operate in a high-frequency region (2.5–3.5 GHz) within a 50 × 50 mm² confined geometric area using characteristic material properties. The sensor was fabricated on Al₂O₃ using screen printing methods and then sintered at 700 °C for Ag and 1200 °C for ITO in an ambient atmosphere. Sensors were evaluated at 600 °C for Ag and 1000 °C for ITO and analyzed at set interrogating distances up to 0.75 m using ultra-wideband slot antennas to collect scattering parameters. The sensitivity (average change in resonant frequency with respect to temperature) from 50 to 1000 °C was between 22 and 62 kHz/°C which decreased as interrogating distances reached 0.75 m. Full article

(This article belongs to the Topic Structural Health Monitoring Based on Materials, Mathematical Methods, and Sensing Technology)

► Show Figures

Figure 1

22 pages, 3152 KiB

Open AccessArticle

Revealing the Proximity of Concrete Specimens to Their Critical Damage Level by Exploring the Cumulative Counts of the Acoustic Emissions in the Natural Time Domain

by Dimos Triantis, Ermioni D. Pasiou, Ilias Stavrakas and Stavros K. Kourkoulis

Materials 2024, 17(5), 1017; https://doi.org/10.3390/ma17051017 - 22 Feb 2024

Viewed by 401

Abstract

This study aims to explore the possibility of detecting indices that could potentially provide warning about the proximity of internal damage to critical levels, beyond which catastrophic fracture is impending. In this direction, advantage was taken of the Cumulative Counts that were recorded during the mechanical loading of specimens made of either plain or fiber-reinforced concrete. The parameter adopted for the analysis was the average rate of change in the Cumulative Counts. Τhe evolution of the specific parameter was considered in the Natural Time Domain, rather than in the conventional time domain. Experimental data from already published three-point bending protocols were used. It was revealed that the specific parameter attains, systematically, a limiting value equal to unity exactly at the instant at which the load reaches its maximum value, which is not identical to the load recorded at the instant of fracture. Similar observations were made for a complementary protocol with uniaxially compressed mortar specimens. The conclusions drawn were supported by the b-values analysis of the respective acoustic data, again in terms of Natural Time. It is, thus, indicated that the evolution of the average rate of change in the Cumulative Counts in the Natural Time Domain provides an index about the proximity of the applied load to a value beyond which the specimen enters into the critical state of impending fracture. Full article

(This article belongs to the Topic Structural Health Monitoring Based on Materials, Mathematical Methods, and Sensing Technology)

► Show Figures

Figure 1

18 pages, 13551 KiB

Open AccessArticle

Enhanced Strain Field Reconstruction in Ship Stiffened Panels Using Optical Fiber Sensors and the Strain Function-Inverse Finite Element Method

by Qingfeng Zhu, Guoqing Wu, Jie Zeng, Zhentao Jiang, Yingping Yue, Chao Xiang, Jun Zhan and Bohan Zhao

Appl. Sci. 2024, 14(1), 370; https://doi.org/10.3390/app14010370 - 30 Dec 2023

Viewed by 734

Abstract

Accurately reconstructing the strain field within stiffened ship panels is crucial for effective structural health monitoring. This study presents a groundbreaking approach to strain field reconstruction in such panels, utilizing optical fiber sensors in conjunction with the strain function-inverse finite element method (SF-iFEM). A novel technique for solving nodal strain vectors, based on the element strain function, has been devised to improve the accuracy of strain reconstruction using the inverse finite element method (iFEM), addressing the limitations associated with traditional nodal displacement vector solutions. Moreover, the proposed method for determining the equivalent neutral layer of stiffened ship panels not only reduces the number of elements effectively but also establishes a strain function between the inner and outer surfaces of the structure. Using this function, a layout scheme for optical fiber sensors on the inner side of ship stiffened panels is provided, overcoming the symmetrical arrangement constraints of iFEM for sensor placement on both the inner and outer sides of the structure. The results demonstrate a significant improvement in strain reconstruction accuracy under bending and bending–torsion deformations compared to conventional iFEM. Consequently, the findings of this research will contribute to enhancing the engineering applicability of iFEM in ship structure health monitoring. Full article

(This article belongs to the Topic Structural Health Monitoring Based on Materials, Mathematical Methods, and Sensing Technology)

► Show Figures

Figure 1

15 pages, 1365 KiB

Open AccessArticle

The Challenges and Advantages of Distributed Fiber Optic Strain Monitoring in and on the Cementitious Matrix of Concrete Beams

by Martin Weisbrich, Dennis Messerer and Klaus Holschemacher

Sensors 2023, 23(23), 9477; https://doi.org/10.3390/s23239477 - 28 Nov 2023

Viewed by 774

Abstract

Distributed fiber optic strain measurement techniques have become increasingly important in recent years, especially in the field of structural health monitoring of reinforced concrete structures. Numerous publications show the various monitoring possibilities from bridges to special heavy structures. The present study is intended to demonstrate the possibilities, but also the challenges, of distributed fiber optic strain measurement in reinforced concrete structures. For this purpose, concrete beams for 3-point bending tests were equipped with optical fibers on the reinforcement and concrete surface as well as in the concrete matrix in order to record the strains in the compression and tension zone. In parallel, an analytical approach based on the maximum strains in the uncracked and cracked states was performed using the Eurocode 2 interpolation coefficient. In principle, the structural design correlates with the measured values, but the strains are underestimated, especially in the cracked zone. During load increase, structural distortions in the compression zone affected the strain signal, making reliable evaluation in this zone difficult. The information content of distributed fiber optic strain measurement in reinforced concrete structures can offer tremendous opportunities. Future research should consider all aspects of the bond, sensor selection and positioning. In addition, there is a lack of information on the long-term stability of the joint and the fiber coating, as well as the effects of dynamic loading. Full article

(This article belongs to the Topic Structural Health Monitoring Based on Materials, Mathematical Methods, and Sensing Technology)

► Show Figures

Figure 1

20 pages, 4984 KiB

Open AccessArticle

Study of the Reasonable Acquisition Frequency Evaluation Method of Midspan Deflection of Medium- and Small-Span Beam Bridges

by Zhengjun Tan, Haijun Wu and Qingcui Tang

Appl. Sci. 2023, 13(22), 12197; https://doi.org/10.3390/app132212197 - 10 Nov 2023

Viewed by 610

Abstract

The objective of this study is to further promote and apply the structural monitoring system to medium and small bridges, given the relative delays in scientific research, technical specifications, and engineering practice for the safety monitoring of small and medium-span girder bridges, as well as the relative simplicity of the structural system of these bridges, their well-defined forces, and the relatively large proportion of live load responses during operation. These concepts are proposed based on the evaluation method of live loading (As therefore, this paper suggests the notion of sensor acquisition frequency and appropriate acquisition frequency based on the live load assessment method and the fundamental reliability theory). Based on the time-history curve depicting the midspan deflection response of the vehicle-bridge coupling system, the frequency domain analysis reveals that the power spectrum at −3 dB corresponds to the response cutoff frequency. Significantly, the cutoff frequency mentioned is double the acquisition frequency considered suitable for the study. Based on the definition of a quasi-static response, it can be deduced that the velocity of a load does not exert any influence on the quasi-static response of a bridge structure. As a result, the derivation of the components related to the midspan deflection of a bridge’s quasi-static response is presented, together with a recommended set of methodological guidelines for the extraction of finite elements. This study introduces a novel approach for determining the cutoff frequency of the structural response by utilizing the characteristics of amplitude spectrum estimation and power spectrum estimation in frequency domain analysis. The cutoff frequency of the signal is determined by analyzing the amplitude-frequency curve of the power spectrum. Subsequently, the probability density function of the original time-history curve data is estimated based on the amplitude spectrum. Finally, reliability analysis is conducted by calculating the ratio of the amplitude spectrum area of the signal obtained through a reasonable acquisition frequency to the area of the amplitude spectrum function of the original signal. This analysis verifies the reliability of the proposed method for determining the midspan deflection acquisition frequency. Full article

(This article belongs to the Topic Structural Health Monitoring Based on Materials, Mathematical Methods, and Sensing Technology)

► Show Figures

Figure 1

21 pages, 7637 KiB

Open AccessArticle

An Integrated Method for Tunnel Health Monitoring Data Analysis and Early Warning: Savitzky–Golay Smoothing and Wavelet Transform Denoising Processing

by Ning Zhao, Jincheng Wei, Zhiyou Long, Chao Yang, Jiefu Bi, Zhaolong Wan and Shi Dong

Sensors 2023, 23(17), 7460; https://doi.org/10.3390/s23177460 - 28 Aug 2023

Viewed by 889

Abstract

A tunnel health monitoring (THM) system ensures safe operations and effective maintenance. However, how to effectively process and denoise several data collected by THM remains to be addressed, as well as safety early warning problems. Thus, an integrated method for Savitzky–Golay smoothing (SGS) and Wavelet Transform Denoising (WTD) was used to smooth data and filter noise, and the coefficient of the non-uniform variation method was proposed for early warning. The THM data, including four types of sensors, were attempted using the proposed method. Firstly, missing values, outliers, and detrend in the data were processed, and then the data were smoothed by SGS. Furthermore, data denoising was carried out by selecting wavelet basis functions, decomposition scales, and reconstruction. Finally, the coefficient of non-uniform variation was employed to calculate the yellow and red thresholds. In data smoothing, it was found that the Signal Noise Ratio (SNR) and Root Mean Square Error (RMSE) of SGS smoothing were superior to those of the moving average smoothing and five-point cubic smoothing by approximately 10% and 30%, respectively. An interesting phenomenon was discovered: the maximum and minimum values of the denoising effects with different wavelet basis functions after selection differed significantly, with the SNR differing by 14%, the RMSE by 8%, and the r by up to 80%. It was found that the wavelet basis functions vary, while the decomposition scales are consistently set at three layers. SGS and WTD can effectively reduce the complexity of the data while preserving its key characteristics, which has a good denoising effect. The yellow and red warning thresholds are categorized into conventional and critical controls, respectively. This early warning method dramatically improves the efficiency of tunnel safety control. Full article

(This article belongs to the Topic Structural Health Monitoring Based on Materials, Mathematical Methods, and Sensing Technology)

► Show Figures

Figure 1

25 pages, 5751 KiB

Open AccessArticle

Electroencephalographic Characterization by Covariance Analysis in Men with Parkinson’s Disease Reveals Sex- and Age-Related Differences

by Gabriela González-González, Víctor Manuel Velasco Herrera and Alicia Ortega-Aguilar

Appl. Sci. 2023, 13(17), 9618; https://doi.org/10.3390/app13179618 - 25 Aug 2023

Viewed by 658

Abstract

Parkinson’s disease (PD) is the fastest growing neurological disease associated with ageing; its symptomatology varies between sexes. Several quantitative electroencephalography analyses have been used to study the early stages and progression of PD. In this study, we aim to characterize the brain activity by considering the five brainwaves in an eyes-closed resting state, using covariance wavelet analysis (CWA) of electroencephalographic records (EEGs) to analyze the influence of sex and age. To effectively eliminate artifacts from the EEG dataset and extract pertinent brain activity, we employ the inverse wavelet analysis. EEGs from men with PD were divided into two age groups (PD < 60 and PD > 60 years old) with their respective age-matched controls (CL). Brain activity patterns in frequency and power domains were analyzed with the CWA. Main frequency profiles, global wavelet curves, power anomalies, and power per brainwave were used to illustrate the CWA patterns. Power anomalies were used to generate anteroposterior power gradients. In PD < 60 men, frequency and power for the α brainwave decreased, while the δ brainwave increased. The θ brainwave increased and was dominant over the α brainwave in PD > 60 men. The anteroposterior power gradient in PD < 60 men had a positive slope, but it was negative in CL. In both PD and CL > 60 men, the anteroposterior gradient was negative. In PD > 60 men, the θ brainwave increased and became dominant. Men with PD had twice the θ brainwave increase. An inverse relationship between α and δ brainwaves was detected in a PD < 60 sex comparison. A conventional EEG spectral analysis using CWA indicated significant differences in brain activity patterns in the PD/CL groups affected by sex and age, yielding previously unknown information. Full article

(This article belongs to the Topic Structural Health Monitoring Based on Materials, Mathematical Methods, and Sensing Technology)

► Show Figures

Figure 1

14 pages, 4289 KiB

Open AccessArticle

Evaluating Structural Details’ Influence on Elastic Wave Propagation for Composite Structures via Ray Tracing

by Fernando Sánchez Iglesias and Antonio Fernández López

Sensors 2023, 23(16), 7220; https://doi.org/10.3390/s23167220 - 17 Aug 2023

Viewed by 663

Abstract

This study presents a novel method based on ray tracing for analyzing wave propagation in composites specifically tailored for structural health monitoring applications. This method offers distinct advantages over the commonly used finite element method mainly in computational resource utilization, which has become a limiting factor for these kinds of analyses. The ray tracing method is evaluated against a number of example cases representing structural details such as thickness changes, stringers, or simulated damage, and the significance of ray tracing to study wave propagation under these conditions and how it can serve as a valuable tool for structural health monitoring are highlighted. This model has been developed as part of a complete SHM framework with the intention of being an efficient and simple way to calculate wave propagation and therefore it could be used as a way to determine relevant damage indicators or train an artificial intelligence model. Full article

(This article belongs to the Topic Structural Health Monitoring Based on Materials, Mathematical Methods, and Sensing Technology)

► Show Figures

Figure 1

19 pages, 12757 KiB

Open AccessArticle

BDS Dual-Frequency Carrier Phase Multipath Hemispherical Map Model and Its Application in Real-Time Deformation Monitoring

by Ao Sun, Qiuzhao Zhang, Xingwang Gao, Xiaolin Meng, Yunlong Zhang and Craig Hancock

Sensors 2023, 23(14), 6357; https://doi.org/10.3390/s23146357 - 13 Jul 2023

Cited by 1 | Viewed by 783

Abstract

The BDS multipath delay error is highly related to the surrounding monitoring environment, which cannot be eliminated or mitigated by applying the double difference observation model. In the actual monitoring environment, due to the complexity of the BDS constellation, it is difficult for existing algorithms to consider GEO, IGSO, MEO and other different orbital types of satellites for real-time and efficient multipath error reduction. Therefore, we propose a novel BDS dual-frequency multipath error reduction method for real deformation monitoring for BDS considering various satellite orbit types. This method extracts the single error residual of each satellite based on the assumption of “zero mean” and divides the appropriate grid density of GEO and IGSO/MEO, respectively, to construct a dual-frequency multipath hemispherical map model suitable for BDS satellites with different orbital types. This method can realize the multipath error elimination of the observed values of different orbits and different frequencies. The results of simulation experiments and real deformation monitoring data demonstrate that this method can effectively eliminate low-frequency multipath delay errors in the observation domain and coordinate domain. After multipath correction, the precision of the horizontal coordinates and height coordinates are 1.7 mm and 4.6 mm. The precision of the horizontal coordinate and height coordinate is increased by 50% and 60%, respectively. The fixed rate of ambiguity increased by 5–7%. Full article

(This article belongs to the Topic Structural Health Monitoring Based on Materials, Mathematical Methods, and Sensing Technology)

► Show Figures

Figure 1

17 pages, 10732 KiB

Open AccessArticle

A New Method for Erosion Prediction of 90° Elbow Based on Non-Axisymmetric Ultrasonic-Guided Wave and the PSO–LSSVM Algorithm

by Zhaokun Wang, Sizhu Zhou, Ning Li, Yun Zeng and Gui Li

Sensors 2023, 23(14), 6311; https://doi.org/10.3390/s23146311 - 11 Jul 2023

Viewed by 803

Abstract

The non-axisymmetric exciting guided wave can detect the thinning section of the elbow, and the time domain energy value of the signal collected at the outer arch position of the receiving end displays a downward trend as the remaining thickness of the erosion area decreases. To address the difficulty in detecting the erosion degree of the elbow with high accuracy, this paper uses the linear frequency modulation (LFM) signal to excite a non-axisymmetric guided wave that propagates in the 90° elbow and collects signals through four PZT receivers. To predict the erosion degree, the corresponding relationship between the energy value of the four signals after fractional Fourier filtering and the degree of elbow erosion is established through the particle swarm optimization (PSO)–least squares support vector machine (LSSVM) algorithm. The results show that the method proposed has an average accuracy rate of 98.1864%, 94.7167%, 99.119%, and 99.9593% for predicting the erosion degree of four elbow samples, and 94.0039%. and 81.2976% for two new erosion degrees, which are higher than the nonlinear regression model, LSSVM algorithm, and BP neural network algorithm. This study has guiding significance for real-time monitoring of elbow erosion. Full article

(This article belongs to the Topic Structural Health Monitoring Based on Materials, Mathematical Methods, and Sensing Technology)

► Show Figures

Figure 1

29 pages, 24046 KiB

Open AccessArticle

LiDAR Point Cloud Data Combined Structural Analysis Based on Strong Form Meshless Method Using Essential Boundary Condition Capturing

by Kyung-Wan Seo, Young-Cheol Yoon and Sang-Ho Lee

Sensors 2023, 23(13), 6063; https://doi.org/10.3390/s23136063 - 30 Jun 2023

Cited by 2 | Viewed by 988

Abstract

This study proposes a novel hybrid simulation technique for analyzing structural deformation and stress using light detection and ranging (LiDAR)-scanned point cloud data (PCD) and polynomial regression processing. The method estimates the edge and corner points of the deformed structure from the PCD. It transforms into a Dirichlet boundary condition for the numerical simulation using the particle difference method (PDM), which utilizes nodes only based on the strong formulation, and it is advantageous for handling essential boundaries and nodal rearrangement, including node generation and deletion between analysis steps. Unlike previous studies, which relied on digital images with attached targets, this research uses PCD acquired through LiDAR scanning during the loading process without any target. Essential boundary condition implementation naturally builds a boundary value problem for the PDM simulation. The developed hybrid simulation technique was validated through an elastic beam problem and a three-point bending test on a rubber beam. The results were compared with those of ANSYS analysis, showing that the technique accurately approximates the deformed edge shape leading to accurate stress calculations. The accuracy improved when using a linear strain model and increasing the number of PDM model nodes. Additionally, the error that occurred during PCD processing and edge point extraction was affected by the order of polynomial regression equation. The simulation technique offers advantages in cases where linking numerical analysis with digital images is challenging and when direct mechanical gauge measurement is difficult. In addition, it has potential applications in structural health monitoring and smart construction involving machine leading techniques. Full article

(This article belongs to the Topic Structural Health Monitoring Based on Materials, Mathematical Methods, and Sensing Technology)

► Show Figures

Figure 1

Show export options Show export options

Select all

Export citation of selected articles as:

Displaying articles 1-12

Submit your Abstract

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Applied Sciences applsci	2.7	4.5	2011	16.9 Days	CHF 2400
Buildings buildings	3.8	3.1	2011	14.6 Days	CHF 2600
CivilEng civileng	-	2.0	2020	37.7 Days	CHF 1200
Materials materials	3.4	5.2	2008	13.9 Days	CHF 2600
Remote Sensing remotesensing	5.0	7.9	2009	23 Days	CHF 2700
Sensors sensors	3.9	6.8	2001	17 Days	CHF 2600

Topic Menu

Topic Editors

Structural Health Monitoring Based on Materials, Mathematical Methods, and Sensing Technology

Topic Information

Keywords

Participating Journals

Published Papers (12 papers)

Further Information

Guidelines

MDPI Initiatives

Follow MDPI